Identifying resource allocation discrepancies

A system for identifying allocations discrepancies, comprising:

• a network computer, comprising:
• a transceiver that communicates over the network;
• a memory that stores at least instructions;
• and
• one or more processor devices that execute instructions that perform actions, including:
• providing a plurality of data models and a plurality of benchmark models to an analysis engine, wherein the plurality of data models are each comprised of two or more nodes and one or more edges from a memory that is configured and arranged to store the plurality of data models, and wherein each node represents a model object and each edge represents a resource allocation;
• providing one or more discrepancy models to the analysis engine, wherein each discrepancy model includes one or more rules;
• employing the analysis engine to search for discrepancies in the plurality of data models based on the one or more discrepancy models and the plurality of benchmark models;
• and
• when one or more discrepancies are identified by the analysis engine, performing further actions, including:
• providing one or more notifications to one or more users;
• and
• modifying the one or more discrepancy models based on subsequent feedback provided by the one or more users;
• and
• a client computer, comprising:
• a client computer transceiver that communicates over the network;
• a client computer memory that stores at least instructions;
• and
• one or more processor devices that execute instructions that perform actions, including:
• displaying the one or more notifications associated with the one or more identified discrepancies;
• and
• providing the user feedback to the analysis engine criteria.

A processor readable non-transitory storage media that includes instructions for identifying allocation discrepancies, wherein execution of the instructions by one or more hardware processors performs actions, comprising:

• instantiating a resource modeling engine to perform actions, including:
• providing a plurality of data models and a plurality of benchmark models to a separately instantiated analysis engine, wherein the plurality of data models are each comprised of two or more nodes and one or more edges from a memory that is configured and arranged to store the plurality of data models, and wherein each node represents a model object and each edge represents a resource allocation;
• and
• providing one or more discrepancy models to the analysis engine, wherein each discrepancy model includes one or more rules, wherein the analysis engine is employed to search for discrepancies in the plurality of data models based on the one or more discrepancy models and the plurality of benchmark models;
• and
• instantiating a visualization engine to use one or more discrepancies that are identified by the analysis engine to perform further actions, including:
• providing one or more notifications to one or more users, wherein geolocation information based on electronic signals processed by a Global Positioning System (GPS) device is employed to localize a visual display of the notifications based on a location of the one or more users, wherein the localization includes one or more of time zone, currency, calendar format, or language, wherein the resource modeling engine modifies the one or more discrepancy models based on subsequent feedback provided by the one or more users in the visual display.

A network computer for identifying allocation discrepancies, comprising:

• a transceiver that communicates over the network;
• a memory that stores at least instructions;
• and
• one or more processor devices that execute instructions that perform actions, including:
• instantiating a resource modeling engine to perform actions, including:
• providing a plurality of data models and a plurality of benchmark models to a separately instantiated analysis engine, wherein the plurality of data models are each comprised of two or more nodes and one or more edges from a memory that is configured and arranged to store the plurality of data models, and wherein each node represents a model object and each edge represents a resource allocation;
• and
• providing one or more discrepancy models to the analysis engine, wherein each discrepancy model includes one or more rules, wherein the analysis engine is employed to search for discrepancies in the plurality of data models based on the one or more discrepancy models and the plurality of benchmark models;
• and
• instantiating a visualization engine to use one or more discrepancies that are identified by the analysis engine to perform further actions, including:
• providing one or more notifications to one or more users, wherein geolocation information based on electronic signals processed by a Global Positioning System (GPS) device is employed to localize a visual display of the notifications based on a location of the one or more users, wherein the localization includes one or more of time zone, currency, calendar format, or language, wherein the resource modeling engine modifies the one or more discrepancy models based on subsequent feedback provided by the one or more users in the visual display.